Acute ischemic stroke is a major disease and one of
the leading causes of adult death and disability. Final outcome prediction is
hampered by the heterogeneity and physiological complexity of stroke progression.
Convolutional neural networks have shown promising results in final outcome
predictions. However, less attention has been paid to the generalizability of
the results across patient cohorts. We test the applicability of an existing
neural network trained on two clinical studies to completely independent cohort
from the DEFUSE 2 trial. We examine how a few additional patients can be used
to obtain performance comparable to the original studies.

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